Arid
DOI10.1016/j.rse.2020.111734
Evaluation and analysis of SMAP, AMSR2 and MEaSUREs freeze/thaw products in China
Wang, Jian; Jiang, Lingmei; Cui, Huizhen; Wang, Gongxue; Yang, Jianwei; Liu, Xiaojing; Su, Xu
通讯作者Jiang, LM
来源期刊REMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
EISSN1879-0704
出版年2020
卷号242
英文摘要The surface seasonal freeze/thaw (F/T) signal detected by passive microwave remote sensing is very important for the water cycle, carbon cycle and climate change research. In this study, we evaluated and analyzed the Soil Moisture Active Passive (SMAP) L3 F/T product, Advanced Microwave Scanning Radiometer 2 (AMSR2) F/T product and Making Earth System Data Records for Use in Research Environments (MEaSUREs) F/T product over different regions in China, including the Genhe area in Northeast China, the Saihanba area in North China, and the Qinghai-Tibet Plateau (QTP) area. The overall accuracy of F/T products assessed with the 5 cm depth soil temperature is 90.38% for SMAP, 90.23% for AMSR2 and 84.73% for MEaSUREs in cold and humid temperate forest climates and the plateau continental climate area (Genhe, Tianjun, and Qumalai) where permafrost is distributed, and 76.64% for SMAP, 83.67% for AMSR2 and 77.37% for MEaSUREs in the cold plateau mountain climate and plateau continental climate area (Saihanba and Chengduo) with frozen ground distributed seasonally, respectively. The overall accuracy is 69.05% for SMAP, 76.5% for AMSR2 and 81.4% for MEaSUREs in the Ngari, Naqu, and Dachaidan regions belonging to arid and semi-arid climates. It can be seen that SMAP and AMSR2 achieve the best performance in the distributed permafrost area, the second-best performance in the seasonal distributed permafrost area, but the worst performance in the areas with arid and semi-arid climate types due to inconsistent F/T signals between water with small changes and temperature with apparent changes during the F/T transition. The MEaSUREs product showed almost the same performance in different regions, indicating that it was less affected by climate types and the distribution of frozen soil than SMAP and AMSR2 products. SMAP F/T product detected by L-band with long penetration and AMSR2 F/T product calibrated with 5 cm soil temperature could represent the 5 cm F/T, but the MEaSUREs F/T product was more likely to describe the surface F/T state due to calibrated with air temperature and the short penetration of 36.5 GHz. In mid-low latitude areas (Tianjun and Qumalai) with a short duration of snow cover days and a fast snowmelt, the effect of snow melting on F/T products was negligible. Moreover, the spring snowmelt affects the three F/T products in Chengduo, but the SMAP product is not affected by the winter snowmelt, whereas the AMSR2 product is affected by the winter snowmelt.
英文关键词SMAP AMSR2 MEaSUREs Evaluation Freeze/thaw China
类型Article
语种英语
收录类别SCI-E
WOS记录号WOS:000523965600014
WOS关键词LAND-SURFACE-TEMPERATURE ; SOIL-MOISTURE ; BRIGHTNESS TEMPERATURES ; SPATIAL VARIABILITY ; TIBETAN PLATEAU ; DATA RECORD ; SATELLITE ; LANDSCAPE ; RADAR ; VALIDATION
WOS类目Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构北京师范大学
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/324316
作者单位[Wang, Jian; Jiang, Lingmei; Cui, Huizhen; Wang, Gongxue; Yang, Jianwei; Liu, Xiaojing; Su, Xu] Beijing Normal Univ, Jointly Sponsored Beijing Normal Univ & Inst Remo, State Key Lab Remote Sensing Sci, Chinese Acad Sci,Fac Geog Sci, Beijing 100875, Peoples R China
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GB/T 7714
Wang, Jian,Jiang, Lingmei,Cui, Huizhen,et al. Evaluation and analysis of SMAP, AMSR2 and MEaSUREs freeze/thaw products in China[J]. 北京师范大学,2020,242.
APA Wang, Jian.,Jiang, Lingmei.,Cui, Huizhen.,Wang, Gongxue.,Yang, Jianwei.,...&Su, Xu.(2020).Evaluation and analysis of SMAP, AMSR2 and MEaSUREs freeze/thaw products in China.REMOTE SENSING OF ENVIRONMENT,242.
MLA Wang, Jian,et al."Evaluation and analysis of SMAP, AMSR2 and MEaSUREs freeze/thaw products in China".REMOTE SENSING OF ENVIRONMENT 242(2020).
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